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作者： Bai, Ting Johansson, Alexander Li, Shaoyuan Johansson, Karl Henrik Mårtensson, Jonas School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden KTH Royal Institute of Technology Stockholm Sweden Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Digital Futures Stockholm Sweden

This paper models a platooning system consisting of trucks and a third-party service provider (TPSP), which performs platoon coordination, distributes the platooning profit in platoons, and charges trucks in exchange for the services. Government subsidies used to incentivize platooning are also considered. We propose a pricing rule for the TPSP, which keeps part of the platooning profit including the subsidy each time a platoon is formed. In addition, a platoon coordination solution based on the distributed model predictive control (MPC) is proposed, in which the pricing rule under government subsidies is integrated. We perform a realistic simulation over the Swedish road network to evaluate the impact of the pricing rule and subsidies on the achieved profits and fuel savings. Our results show that subsidies are an effective mean to boost fuel savings from platooning. Moreover, the simulation study indicates that high pricing corresponds to a low platooning rate of the system, as trucks' incentives for platooning decrease. © 2023 The Authors. Asian Journal of control published by John Wiley & Sons Australia, Ltd on behalf of Chinese Automatic control Society.

关键词： Trucks

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Virtualizing Next-Generation Programmable Networks: Techniques, Use Cases, and Promising Future Directions

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IEEE Network 2025年第3期39卷 148-155页

作者： Chen, Xiang Du, Hongyang Liu, Wenjing Liu, Hongyan Zhang, Jianshan Yang, Xu Zhang, Dong Wu, Chunming Liu, Xuan Niyato, Dusit Zhejiang University College of Computer Science and Technology Hangzhou310027 China The University of Hong Kong Department of Electrical and Electronic Engineering Pokfulam Hong Kong Zhejiang Media Group Hangzhou310005 China Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Data Science Fuzhou350108 China Fuzhou University College of Computer and Data Science Fuzhou350108 China Yangzhou University College of Information Engineering College of Artificial Intelligence Yangzhou225009 China Nanyang Technological University College of Computing and Data Science Jurong West 639798 Singapore

For decades, network virtualization plays a crucial role in modern networks, e.g., 6G mobile networks: tenants construct arbitrary virtual networks on the same physical network. However, production networks are becoming programmable and need more ways of network configurations. So prior techniques like SDN hypervisors are deprecated since they cannot configure programmable networks. In response, a new category of network virtualization techniques has emerged recently to virtualize programmable networks, i.e., programmable network hypervisors (PNHs). This article first reviews this trend to comprehensively survey PNHs. To understand their benefits, we build a testbed with hardware switches and sophisticated topologies. Our testbed experiments stress-test hypervisors and demonstrate that they outperform prior works with higher acceptance ratios of virtual networks under large-scale scenarios and heavy loads. Finally, we highlight the open issues of these techniques to shed light on the future directions in this promising topic. © 1986-2012 IEEE.

关键词： Virtualization

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Symbiotic control of Uncertain Dynamical systems: Harnessing Synergy Between Fixed-Gain control and Adaptive Learning Architectures

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IEEE Transactions on Automatic control 2025年

作者： Yucelen, Tansel Sarsilmaz, Selahattin Burak Yildirim, Emre University of South Florida Department of Mechanical Engineering Laboratory for Autonomy Control Information and Systems TampaFL33620 United States Utah State University Department of Electrical and Computer Engineering LoganUT84322 United States

Both fixed-gain control and adaptive learning architectures aim to mitigate the effects of uncertainties. In particular, fixed-gain control offers more predictable closed-loop system behavior but requires the knowledge of uncertainty bounds. In contrast, while adaptive learning does not necessarily require such knowledge, it often results in less predictable closed-loop system behavior compared to fixed-gain control. To this end, this paper presents a novel symbiotic control framework that offers the strengths of fixed-gain control and adaptive learning architectures. Specifically, this framework synergistically integrates these architectures to mitigate the effects of uncertainties in a more predictable manner as compared to adaptive learning alone and it does not require any knowledge on such uncertainties. Both parametric and nonparametric uncertainties are considered, where we utilize neural networks to approximate the unknown uncertainty basis for the latter case. Counterintuitively, the proposed framework has the ability to achieve a desired level of closed-loop system behavior even with an insufficient number of neurons (e.g., when the neural network approximation error is large) or in the face of injudiciously selected adaptive learning parameters (e.g., high leakage term parameters). © 1963-2012 IEEE.

关键词： Closed loop control systems

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Distributed Prescribed-Time Observer for Nonlinear systems in Block-Triangular Form

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IEEE control systems Letters 2025年 9卷 222-227页

作者： Vincent de Heij M. Umar B. Niazi Karl H. Johansson Saeed Ahmed Jan C. Willems Center for Systems and Control and the Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Groningen The Netherlands Division of Decision and Control Systems Digital Futures KTH Royal Institute of Technology Stockholm Sweden Department of Electrical Engineering and Computer Science Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA USA

This letter proposes a design of a distributed prescribed-time observer for nonlinear systems representable in a block-triangular observable canonical form. Using a weighted average of neighbor estimates exchanged over a strongly connected digraph, each observer estimates the system state despite the limited observability of local sensor measurements. The proposed design guarantees that distributed state estimation errors converge to zero at a user-specified convergence time, irrespective of observers’ initial conditions. To achieve this prescribed-time convergence, distributed observers implement time-varying local output injection gains that monotonically increase and approach infinity at the prescribed time. The theoretical convergence is rigorously proven and validated through numerical simulations, where some implementation issues due to increasing gains have also been clarified.

关键词： Observers Convergence Nonlinear systems Symmetric matrices Observability Directed graphs control systems Vectors Linear systems Electronic mail

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UW-DNeRF: Deformable Soft Tissue Reconstruction with Uncertainty-Guided Depth Supervision and Local information Integration

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IEEE Transactions on Medical Imaging 2025年 PP卷 PP页

作者： Shan, Jiwei Zhang, Zixin Li, Hao Hsieh, Cheng-Tai Li, Yirui Wu, Wenhua Wang, Hesheng School of Electronic Information and Electrical Engineering of Shanghai Jiao Tong University Shanghai200240 China Shanghai Jiao Tong University School of Mechanical Engineering Shanghai200240 China Shanghai Jiao Tong University State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240 China

Reconstructing deformable soft tissues from endoscopic videos is a critical yet challenging task. Leveraging depth priors, deformable implicit neural representations have seen significant advancements in this field. However, depth priors from pre-Trained depth estimation models are often coarse, and inaccurate depth supervision can severely impair the performance of these neural networks. Moreover, existing methods overlook local similarities in input sequences, which restricts their effectiveness in capturing local details and tissue deformations. In this paper, we introduce UW-DNeRF, a novel approach utilizing neural radiance fields for high-quality reconstruction of deformable tissues. We propose an uncertainty-guided depth supervision strategy to mitigate the impact of inaccurate depth information. This strategy relaxes hard depth constraints and unlocks the potential of implicit neural representations. In addition, we design a local window-based information sharing scheme. This scheme employs local window and keyframe deformation networks to construct deformations with local awareness and enhances the model's ability to capture fine details. We demonstrate the superiority of our method over state-of-The-Art approaches on synthetic and in-vivo endoscopic datasets. Code is available at: https://***/IRMVLab/UW-DNeRF. © 2025 IEEE.

关键词： Endoscopy

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Error-Accumulation Improved Newton Algorithm in Model Predictive control for Novel Compliant Actuator-Driven Upper-Limb Exoskeleton

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Tsinghua Science and Technology 2025年第5期30卷 1965-1979页

作者： Changxian Xu Jiliang Zhang Keping Liu Jian Wang Zhongbo Sun Department of Mechanical and Electrical Engineering Changchun University of Technology Changchun China College of Information Science and Engineering Northeastern University Shenyang China National Mobile Communications Research Laboratory Southeast University Nanjing China School of Electrical and Information Engineering Jilin Engineering Normal University Changchun China Laboratory of Cognitive and Decision Intelligence for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Control Engineering Changchun University of Technology Changchun China

In this paper, a Novel Compliant Actuator (NCA)-driven Upper-Limb Exoskeleton (ULE) with force controllable, impact resistance, and back drivability is designed to ensure the safety of the subject during Human-Robot Interaction (HRI) processing. Based on the designed NCA-driven ULE, this paper constructs a Model Predictive control Scheme (MPCS) for force trajectory tracking, which minimises future tracking errors by solving an optimal control problem with inequality constraints. In addition, an Error-Accumulation Improved Newton Algorithm (EAINA) is proposed to solve the MPCS for suppressing various noises and external disturbances. The proposed EAINA is theoretically proved to have small steady state for noise conditions and stability of the EAINA using Lyapunov method. Finally, experimental results verify that the proposed MPCS solved by the EAINA in the NCA-driven ULE achieves robustness, fast convergence, strong tolerance and stability for trajectory rehabilitation task.

关键词： Actuators Trajectory tracking Noise Exoskeletons Force Human-robot interaction Prediction algorithms Stability analysis Robustness Predictive control

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A Parallel Read-Write Circuit With Fast Amplitude-Adaptive Matching Scheme to Memristor Crossbar Array

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IEEE Transactions on Circuits and systems I: Regular Papers 2025年

作者： Jiang, Ningye Jiang, Mingxuan Huang, Haoen Yang, Le Huang, Yi Zeng, Zhigang Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education of China Wuhan430074 China Wuhan Institute of Technology School of Electrical and Information Engineering Wuhan430205 China University of Massachusetts Amherst Department of Electrical and Computer Engineering AmherstMA01003 United States

Memristor crossbar array (MCA) is a computing-in-memory (CIM) module for computational acceleration. However, conventional read-write (R-W) circuits for MCA rely heavily on external components and have shortcoming in long writing times. To address these issues, we propose a parallel R-W circuit with a fast amplitude-adaptive matching (AAM) scheme. The fast AAM scheme is designed to accelerate time of writing memristors in MCA by adaptively adjusting the writing voltage to match an optimal amplitude. The architecture of parallel R-W circuit are outlined with the implementation of R-W processes. The design principles of parallel R-W unit, fast AAM unit, and associated control logic are described for analyzing their functions within the circuit. By integrating the parallel R-W circuit with MCA, a computing block is leveraged in a neural network for classification tasks. The experimental results demonstrate that the neural network with multiple computing blocks maintains high accuracy across various datasets (over 80%). Furthermore, the proposed AAM scheme achieves an average 54% reduction in writing time compared to that one without AAM scheme. Compared to the pulse-width scheme, the parallel R-W circuit exhibits an average 3.05× speedup in adjusting a 5×5 MCA, and the speedup efficiency is higher as the increases of MCA size. © 2025 IEEE.

关键词： Memristors

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A Planar, Wideband and Compact Hadamard Matrix for 2-D Switched Beam Antenna Array

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IEEE Antennas and Wireless Propagation Letters 2025年

作者： Pan, Yufei Xu, Zizhen Yang, Ye Dai, Xin Yang, Wanjun Zheng, Shaoyong School of Electronics and Communication Engineering Guangzhou University Guangzhou China City University of Hong Kong Department of Electrical Engineering Hong Kong Sun Yat-sen University Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems School of Electronics and Information Technology Guangzhou510006 China

This letter proposes a wideband two-dimensional (2-D) switched beam antenna array with single/dual/quad-lobed switched beams for direction of arrival (DOA) estimation. A planar and compact 4-order Hadamard matrix (HM) without any intersection structure works as its feeding network. The HM provides four groups of output signals with equal amplitudes and coded 0° /180° phase differences between adjacent outputs. It adopts four universal building blocks arranged planarly, each of them is realized by a 3-dB wideband quadrature coupler cascading with a 90 8 phase shifter. For demonstration, a HM prototype operating at 2.4 GHz is designed, fabricated, and measured. Its overall circuit size is 0.67 × 1.34 λg 2 and bandwidth is larger than 47.6%. Finally, a wideband 2-D switched beam antenna array is constructed by the proposed HM and magnetoelectric dipole antenna array. The 2-D single/dual/quadlobed switched beams verify its effectiveness. © 2002-2011 IEEE.

关键词： Hadamard matrices

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Performance-Aware control of Modular Batteries For Fast Frequency Response

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IEEE Transactions on Sustainable Energy 2025年

作者： He, Yutong Ruan, Guangchun Zhong, Haiwang Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing100084 China Massachusetts Institute of Technology Lab for Information and Decision Systems CambridgeMA02139 United States

Modular batteries can be aggregated to deliver frequency regulation services for power grids. Although utilizing the idle capacity of battery modules is financially attractive, it remains challenging to consider the heterogeneous module-level characteristics such as dynamic operational efficiencies and battery degradation. In addition, real-time decision making within seconds is required to enable fast frequency response. In order to address these issues, this paper proposes a performance-aware scheduling approach for battery modules to deliver fast frequency response (FFR) support. In particular, the conduction loss and switching loss of battery packs as well as converters are captured within a mix-integer quadratic constrained program (MIQCP). The cycle-based aging model identifies the aging cost of battery modules during frequent cycling by introducing the aging subgradient calculation and linearization. Case studies based on real-world battery data show that the proposed scheduling approach can effectively reduce power loss cost by nearly 28%-57% and battery aging cost by 4%-15% compared to conventional methods, which can also enhance the SoC balance. © 2010-2012 IEEE.

关键词： Battery management systems

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Distributed Fault-Tolerant Formation Game for Quadrotor UAVs With Hybrid Attacks

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Zhang, Rui-Ming Yao, Xiang-Yu Wang, Leimin Park, Ju H. Ge, Ming-Feng China University of Geosciences School of Mechanical Engineering and Electronic Information Wuhan430074 China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China China University of Geosciences School of Automation Wuhan430074 China Yeungnam University Department of Electrical Engineering Gyeongsan38541 Korea Republic of

This manuscript studies the distributed faulttolerant formation for quadrotor unmanned aerial vehicles (QUAVs) subject to actuator failures and hybrid cyber attacks via a game-theoretical approach. The desired formation, which aligns with optimal self-interests, is achieved by seeking the Nash equilibrium (NE) of the game under a strongly connected directed graph. First, a secure fault-tolerant NE seeking algorithm is presented to handle actuator failures and false data injection (FDI) attacks, with the false data being measured through extended state observers (ESOs). The proposed algorithm is established on pseudo-gradient dynamics, in which a local estimate law is used to anticipate the actions of other QUAVs. Then, an ESOsbased algorithm is developed to mitigate the influence of FDI and denial-of-service (DoS) attacks, guaranteeing that all QUAVs exponentially converge to an adjustable small domain of NE by Lyapunov stability analysis. This work is distinct from existing studies by addressing the practical scenario, where physical failures and hybrid cyber attacks occur simultaneously in the game framework of QUAVs. Eventually, numerical experiments are conducted to demonstrate the efficacy of theoretical findings. © 1965-2011 IEEE.

关键词： Drones

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